Ensemble forecast spread induced by soil moisture changes

The impact to soil moisture conditions under three distinct synoptic conditions and forcing over the Ohio River valley was investigated with the aid of a regional atmospheric model coupled to a land surface model during three different synoptic conditions. The study served to put in perspective the potential impact that soil moisture perturbations had on the statistical spread of an ensemble forecast for three different synoptic events during the summer of 2006. Soil moisture was perturbed from a control simulation to generate a 12 member ensemble with 6 members having drier soil and 6 members having moister soil. The impacts on the near-surface atmospheric conditions and on precipitation were analyzed. It was found, as previous studies have confirmed, that soil moisture can change the spatial and temporal distribution of precipitation and of the overlying circulation to an extent that depends on the current synoptic conditions and lifting mechanisms present. Because of the potential impact that soil moisture has on the evolution of the atmosphere and to short-range forecast, a temporal analysis of the spatial correlation and root mean-square difference was proposed to measure the ability of soil moisture to modify the spread of an ensemble prediction system. It was found that regardless of the conditions in synoptic forcing, temperature, relative humidity and horizontal wind field exhibited a spatial correlation coefficient (R) close to one with respect to the control simulation. Vertical velocity, however, showed a marked decrease in R down to 0.4 as the precipitation activity increased. The normalized root-mean square difference (RMSD), between the control and the full ensemble, normalized with respect to the standard deviation of the control, did increase to about 0.4 with respect to the control simulation for all variables as convective activity increased. For vertical velocity, however, this quantity grew to near 1.0 consistent with R near zero and standard deviations very close to that of the control. These results suggested a more complex picture in which soil moisture perturbations played a major role in modifying precipitation and the near-surface circulation but did not broaden the statistical spread of trajectories in phase space of all variables that are part of an ensemble prediction system. -->